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中国生物医学工程学会
北京玛格泰克科技发展有限公司
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2021 Vol. 30, No. 4
Published: 2021-12-30
Research papers
Research papers
139
Human β-defensin-2 Enhances Anti-tumor Efficacy of Survivin-based Broad-spectrum DNA Vaccine in Mouse Tumor Model
LUO Yan-xi, WANG Ming-long, WANG Shi-bing, SUN Ting, XIE Tian, YAN Hui
Objective:
Malignant tumors greatly endanger and affect the quality of human life. Among antitumor biotherapy strategies, DNA vaccines hold promise in part because of their unique advantages. In this study, an effective broad-spectrum antitumor DNA vaccine expressing human survivin T34A dominant-negative mutant fused with human β-defensin-2 (HBD2) was investigated.
Methods:
The expression profiles of genes of interest were examined using western blotting, reverse transcription-polymerase chain reaction (RT-PCR), and enzyme-linked immunosorbent assay (ELISA) in vitro. The immune function of the fusion gene vaccine (FGV) was assessed in BALB/c mice, which included detection of serum antibody, spleen lymphocyte proliferation, interferon-gamma (IFN-γ) secretion, and lactate dehydrogenase (LDH) release. In vivo antitumor effects of FGV were examined in a mouse breast cancer (4T1) model, whereas in vitro effects were assessed using tumor cells derived from different origins. Caspase-3 activity in tumor cells was also assessed after vaccine transfection.
Results:
The FGV triggered humoral as well as cellular immune responses against survivin. It exhibited more potent inhibition of tumor growth as well as prolonged the survival of immunized mice compared to mice immunized with only either survivin T34A or HBD2 vaccines. In addition, FGV displayed stronger cytotoxicity against tumor cells derived from different origins compared to the other vaccines and facilitated increased caspase-3 activity in transfected tumor cells.
Conclusion:
The novel DNA vaccine consisting of a fusion of the universal tumor antigen survivin T34A mutant with molecular adjuvant HBD2 generates enhanced broad-spectrum antitumor efficacy against cancers derived from various origins.
2021 Vol. 30 (4): 139-151 [
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152
Study on the Correlation Between Fracture and Bone Mineral Density Caused by Military Training and the Construction of Prediction Model
WU Ming-hong, WANG Yi-tao, LU Wen-ting
Objective:
Analyze the correlation between the bone mineral density value of army officers and soldiers and the fracture caused by military training, and construct the prediction model of the risk factors of the fracture caused by military training.
Methods:
A total of 1019 officers and soldiers in a military training unit from January 2015 to November 2020 were selected and divided into groups according to whether they were fractured during military training. The basic data were collected in the form of a questionnaire, and the bone mineral density of the forearm and wrist of all subjects were measured by osteosys exa-3000 dual-energy X-ray absorptiometry in Korea. Pearson correlation analysis was used to analyze the correlation between bone mineral density and fractures caused by military training. Multivariate logistic regression was used to analyze the risk factors of fractures caused by military training, build a prediction model, and draw an ROC curve to verify its predictive value for fractures caused by military training.
Results:
There were statistically significant differences between patients with fractures caused by military training and those without fractures in previous fracture history, training period, self-evaluation of training intensity, the intensity of self-protection awareness, and bone mineral density (p<0.05); Multivariate logistic regression analysis showed that past fracture history, training intensity, injury subjects, self-protection awareness, and bone mineral density were all independent factors influencing fractures caused by military training (P<0.05); Pearson correlation analysis showed that bone mineral density was negatively correlated with fractures caused by military training (r=0.686, P<0.01); a predictive model was constructed, model 1 was previous fracture history + training intensity + injury subjects + self-protection awareness, model 2 is the previous fracture history + training intens ity + injury subjects + self-protection awareness + bone mineral density value.The area under the ROC. curve of model 1 and model 2 were 0.729 (0.648-0.785) and 0.893 (0.837-0.914), respectively, and the Youde index were 0.415 and 0.682, respectively.
Conclusion:
There is a negative correlation between bone mineral density and fractures caused by military . training. The prediction value of the fracture prediction model caused by military training constructed by the bone mineral density value is higher.
2021 Vol. 30 (4): 152-161 [
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162
The Concept and Design of Safety Management Innovation in the Use of Medical Equipment: Design of Real-time Monitoring System for Temperature and Humidity of Infant Incubator Based on Internet of Things in China
YIN Jiao-jiao, WANG Xi
Ensuring safety in the use of medical equipment is an important guarantee for clinical diagnosis and treatment. Because medical equipment is mostly electrical and electronic equipment, the suddenness of its failure is inevitable. Although some equipment has regular preventive maintenance and metrological calibration, it is patient-free static calibrated. In China, because of its large population, large patient base, and large use of medical equipment, nurses are too busy taking care of patients and cannot pay attention to the safety of the use of each device. Therefore, we propose using the Internet of Things and IT technology to carry out real-time monitoring and alarming of important parameters of some special, high-risk, and large-used medical equipment, so as to strengthen the safety management of equipment use. Through the management innovation, this article successfully implemented real-time monitoring of the temperature and humidity of the neonatal incubator; and greatly improved the safety in the use of such equipment.
2021 Vol. 30 (4): 162-171 [
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172
Distribution of ApoE Gene Polymorphism and Significance of Auxiliary Diagnosis and Treatment of Cerebrovascular Diseases (Intracerebral Hemorrhage and Cerebral Thrombosis) in the Longyan Area
ZHANG Hong-bin, HE Xiang-sheng, YOU Yu-dong, FAN Zhi-quan, ZHANG Man'e, LU Zhi-hua
Objective:
To make statistics on the distribution of ApoE gene polymorphism in the Longyan area, provide data for the statistics of regional cerebrovascular diseases, explore the significance of ApoE gene polymorphism distribution for clinical guidance, diagnosis and treatment, and provide more suggestions. for clinical diagnosis and treatment of cerebrovascular diseases.
Methods:
800 patients with cerebrovascular disease in the Longyan area from July 2018 to April 2021 were selected as the research object, and 800 normal healthy patients were selected as the control group. The data were further analyzed according to the collected patient information, and the patients were distinguished according to age and other basic information, the type of cerebrovascular disease, ApoE gene polymorphism and blood lipid test results. The distribution of ApoE gene polymorphism in the cerebrovascular disease population in the Longyan area was given to determine the correlation between the incidence of cerebrovascular disease and the distribution of ApoE gene polymorphism.
Results:
In the study group, E2/E3 genotyping was the most common 400 (50.00%), and E4/E4 genotyping 6 (0.75%) was the least common; In the control group, E2/E4 genotyping was the most common 480(60.00%), and E2/E3 genotyping accounted for the second 290 (36.25%). In the study group, E3 allele was the most common 383 (47.88%), E4 allele 121 (15. 12%); in the control group, E2 allele was the most common 391 (48.88%), and E3 allele 142 (17.75%).
Conclusion:
According to the statistics of ApoE gene polymorphism distribution in the Longyan area and the analysis of the correlation of other cerebrovascular diseases, it is found that E2/E3 genotype may be related to cerebrovascular diseases, and E3 allele may be a susceptibility factor. Through the above analysis, the occurrence of diseases can be predicted and prerevented.
2021 Vol. 30 (4): 172-177 [
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A Convolutional Neural Network Model for Classifying Cardiac Membrane Potential Patterns
E Jun-liang, MA Li-yuan, ZHANG Hong, GUO Ping
Investigation of the electrophysiological mechanisms that induce arrhythmias is one of the most important issues in scientific research. Since computational cardiology allows the systematic dissection of causal mechanisms of observed effects, simulations based on the ionic channel mathematical models have . become one of the most widely used methods. To reduce themanual classification of different types of membrane potential patterns produced during simulations, a convolutional neural network is developed in this paper. The model includes 4 convolution layers, 4 pooling layers and a fully connected layer. An activation function of ReLU is used. Before machine learning, all the pattems are calibrated, cut, and normalized to a uniform format with a size of 256x256. The contour boundary of each pattern is extracted using the maximum between-class variance method. In the examination, the proposed learning algorithm shows a recognition accuracy of 97% on test data set after training.
2021 Vol. 30 (4): 178-184 [
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